Method for enabling energy storage system to participate in energy and frequency combined auxiliary service market

Abstract

The invention discloses a method for an energy storage system to participate in an energy and frequency combined auxiliary service market, and belongs to the technical field of energy storage, and the method comprises the following steps: (1) an energy storage system investment planning model considering a short-term security constraint unit commitment; (2) a combined energy and frequency auxiliary service market mechanism; and (3) the influence of various factors on the investment planning result of the energy storage system is deeply analyzed, the influence of factors such as the frequency response capability of the energy storage system, the renewable energy permeability and the frequency safety margin of the system on the investment planning result is analyzed in detail, and a quantitative basis is provided for market design and an investment method. The model is important and effective in the aspects of determining an optimal energy storage system investment method and guiding system operation, and valuable reference is provided for electric power system operators and decision makers.

Description

Technical Field

[0001] The present invention relates to the field of energy storage, and specifically to a method for an energy storage system to participate in the energy and frequency joint ancillary service market. Background Art

[0002] The intensification of global warming highlights that carbon emissions are the main cause of the climate crisis. According to data from the International Energy Agency, the power industry remains the main contributor to the growth of carbon emissions. By 2024, the carbon emissions of the power industry will account for approximately one-third of the global carbon emissions. To address this issue, the power industry is accelerating the adoption of renewable energy to promote the decarbonization of the power industry. The high penetration of renewable energy poses challenges to the stability of the power system because the inertia of the power system has decreased. This decrease may lead to frequency stability problems. In addition, the intermittency of renewable energy makes the operation of the power system more complex.

[0003] To address these challenges, considering the characteristics of fast response and flexible deployment of the energy storage system, this patent proposes an optimal energy storage system investment strategy planning model to support the system frequency. In addition, this patent also introduces the frequency ancillary service market to encourage the energy storage system to participate in providing various frequency ancillary services. This market not only ensures the quality of frequency regulation but also fully allocates the frequency response capacity of the energy storage system. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for an energy storage system to participate in the energy and frequency joint ancillary service market to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions:

[0006] A method for an energy storage system to participate in the energy and frequency joint ancillary service market includes the following steps:

[0007] First, this application provides an energy storage system investment planning model considering a short-term security-constrained unit commitment model, including:

[0008] An energy storage system investment planning model considering a short-term security-constrained unit commitment model covers three core links: integration of unit short-term operation constraints, balance between safety and economy, and establishment of a mathematical model of the energy storage system.

[0009] In the integration of unit short-term operation constraints, the short-term security-constrained unit commitment model is integrated into the energy storage system investment planning. Considering the frequency safety of the power grid and the safe operation constraints of generators and energy storage systems, the safe operation of generators and energy storage systems is ensured, and the operation constraint conditions considering safety for the energy storage system and generators are formed.

[0010] Based on the above-mentioned operating constraint conditions considering the safety of the energy storage system and the generator, the balance between frequency safety and economy is ensured. While meeting the system frequency safety requirements, the model optimizes the investment cost and operating cost of the energy storage system. By simulating multiple typical scenarios and comprehensively considering the system requirements under different operating conditions, the optimal investment strategy of the energy storage system is determined.

[0011] Finally, a mathematical model of the energy storage system is established, with the maximum profit of the energy storage system as the objective function and the charging power, discharging power, etc. of the energy storage system as the optimization variables to establish the mathematical model of the energy storage system.

[0012] In the second aspect, the present application provides a method for introducing a combined energy and frequency ancillary service market mechanism, including:

[0013] An investment planning model for an energy storage system considering a short-term security-constrained unit commitment model, covering three core links: constructing an integrated ancillary service market, reasonably allocating frequency regulation resources, and improving the profit and investment efficiency of the energy storage system.

[0014] In constructing the integrated ancillary service market, the designed combined market includes four flexibility products: energy, inertia, enhanced frequency response, and fixed frequency response, providing economic incentives for the energy storage system to participate in frequency regulation, ensuring the quality of frequency regulation, and making full use of the frequency response ability of the energy storage system.

[0015] On the basis of constructing the integrated ancillary service market, reasonably allocate frequency regulation resources. Based on the pricing mechanism of the Lagrange duality theorem and KKT conditions, determine the marginal price and subsidy price of various electricity products, and reasonably allocate the frequency regulation resources of the energy storage system and traditional thermal power units.

[0016] Finally, improve the profit and investment efficiency of the energy storage system. The energy storage system obtains the profits from the energy market and the frequency ancillary service market through the combined market. Compared with the energy storage system that only participates in the energy market, the profit of the energy storage system participating in the combined market increases significantly, and the investment cost decreases.

[0017] In the third aspect, the present application provides a method for deeply analyzing the influence of various factors on the investment planning of the energy storage system, including:

[0018] Evaluate the influence of the frequency response ability of the energy storage system. By analyzing the influence of the change in the maximum frequency response ability of the energy storage system on the investment planning of the energy storage system, including the capacity demand of the energy storage system, social welfare, investment payback period, etc., determine the optimal ability range to minimize the capacity demand of the energy storage system, maximize social welfare, and shorten the investment payback period.

[0019] Determine the optimal level of renewable energy penetration, study the impact of different renewable energy penetrations on the investment strategy of the energy storage system, determine the optimal value of renewable energy penetration to maximize the benefits of the energy storage system, and optimize the utilization of the frequency regulation resources of the energy storage system.

[0020] Optimize the setting of the system frequency safety margin, explore the impact of the system frequency safety margin on the investment planning of the energy storage system, determine the optimal setting value of the frequency safety margin, so that both the benefits of the energy storage system and the utilization rate of renewable energy reach a relatively high level, indicating that this is the optimal setting of the frequency safety margin.

[0021] Fourthly, the present application provides a decision-making support and market mechanism design suggestion, including:

[0022] Guide the investment decision of the energy storage system. Through numerical research, the importance and effectiveness of the proposed model in determining the optimal investment strategy of the energy storage system are verified. It provides valuable reference for power system operators and decision-makers to help them better understand and plan the investment of the energy storage system.

[0023] Promote the improvement of the market mechanism. The proposed joint market mechanism and pricing strategy provide a theoretical basis and practical guidance for designing a reasonable frequency ancillary service market. It helps to encourage the energy storage system to actively participate in frequency regulation and improve the overall operation efficiency and economy of the power system.

[0024] As a preferred embodiment of the present invention: The short-term operation constraints of the unit are as follows:

[0025]

[0026] In the formula, is the minimum output of the traditional thermal unit, is the maximum output of the traditional thermal unit, P g,t,y is the output of the conventional thermal unit at time t in scenario y, is the binary variable of the operating state of the conventional thermal unit at time t in scenario y, is the binary variable of the startup state of the conventional thermal unit at time t in scenario y, is the binary variable of the shutdown state of the conventional thermal unit at time t in scenario y, is the ramp rate of the traditional thermal unit, is the binary variable of the frequency regulation condition of the conventional thermal unit at time t in scenario y;

[0027] Equation (1) constrains the output of traditional thermal power units, Equation (2) constrains the change of binary variables of the operating conditions of thermal power units, Equations (3)-(4) define the start-up and shutdown constraints of thermal generators, Equation (5) imposes a ramp constraint, Equation (7) gives the production limit of renewable energy, and Equation (8) reflects that thermal power units can provide ancillary services only when in the operating state.

[0028] As a preferred embodiment of the present invention: The planning model considering the inertia and frequency regulation support of the energy storage system under short-term security constraints is as follows:

[0029]

[0030]

[0031] wherein, is the charging power of the energy storage system at time t in scenario y, is the charging power of the energy storage system at time t in scenario y, is the load at time t in scenario y, is the maximum output of the renewable energy unit at time t in scenario y, P r,t,y is the output of the renewable energy unit at time t in scenario y, is the maximum output of the renewable energy unit, is the frequency safety margin, is the frequency regulation power required at time t in scenario y, is the energy price at time t in scenario y, is the inertia price at time t in scenario y, is the price of forced frequency response at time t in scenario y, is the price of fixed frequency response at time t in scenario y, is the dual variable of the frequency change rate equation at time t in scenario y, is the dual variable of the frequency nadir equation at time t in scenario y, is the dual variable of the Q-S-S equation at time t in scenario y, is the binary variable of the charging or discharging condition of the energy storage system at time t in scenario y, is the binary variable of the frequency regulation condition of the traditional thermal unit at time t in scenario y, is the binary variable of the frequency regulation condition of the renewable energy unit at time t in scenario y, is the binary variable of the charging condition of the energy storage system at time t in scenario y, is the binary variable of the discharging condition of the energy storage system at time t in scenario y, H e,t,y is the inertia of the bid at time t in scenario y, H g,t,yThe bidding inertia of the conventional thermal unit at time t in scenario y, H r,t,y is the bidding inertia of the renewable energy generating unit at time t in scenario y, is the total inertia at time t in scenario y, is the inertia constant of the renewable energy unit at time t in scenario y, D e,t,y D r,t,y is the droop coefficient of the renewable energy unit, D g,t,y is the droop coefficient of the unit at time t in scenario y, is the droop coefficient limit at time t in scenario y, is the total droop coefficient at time t in scenario y, is the coefficient of the frequency security margin equation, Δf max is the lowest frequency point, f0 is the base frequency, is the total forced frequency response, EFR g,t,y is the forced frequency response bid of the conventional thermal unit at time t in scenario y, EFR e,t,y is the forced frequency response bid of the energy storage system at time t in scenario y, is the total fixed frequency response, PFR g,t,y is the fixed frequency response bid of the energy storage system at time t in scenario y, PFR e,t,y is the fixed frequency response bid of the energy storage system at time t in scenario y, RoCoF max is the rate of change of frequency, T PFR is the time of the fixed frequency response;

[0032] Equation (9) represents the power balance equation of the system, and its dual variable is the energy market price. Equations (10) and (11) represent the forced frequency response and fixed frequency response generated by the energy storage system and the thermal generator respectively. Equation (12) is the reserve equation of the renewable energy unit. Equation (13) restricts the conditions for the thermal power unit and the renewable energy unit to participate in frequency regulation. Equation (14) constrains the bidding inertia of the renewable energy unit. Equation (15) restricts the droop coefficient provided by the renewable energy. Equation (16) reflects the total inertia of the system. Equation (17) is the frequency security margin constraint of the power system. Equations (18)-(19) constrain the total droop constant of the system. Equation (20) ensures that the rate of change of the system frequency remains within a safe range. Equation (21) is the quasi-steady state frequency constraint. Equation (22) restricts the lowest frequency point of the system simplified from the second-order cone constraint.

[0033] As a preferred solution of the present invention: The Lagrange duality theorem is used to reformulate the equation, where the Lagrange multiplier is used as the dual variable, and the corresponding Lagrange equation is as follows:

[0034]

[0035]

[0036] Equation (23) is the Lagrangian equation of Equation (9), Equation (24) is the Lagrangian equation of Equation (14), Equation (25) is the Lagrangian equation of Equation (10), Equation (26) is the Lagrangian equation of Equation (11), Equation (27) is the Lagrangian equation of Equation (20), Equation (28) is the Lagrangian equation of Equation (21), and Equation (29) is the Lagrangian equation of Equation (22);

[0037] Equations (23)-(26) represent the marginal price required for market participants to produce an additional unit of each electricity product. Equations (27)-(29) reflect the cost required to improve the system security constraint performance by one unit. According to the duality theorem, each term in these equations, including the Lagrangian dual multiplier, can be expressed by the Lagrangian equation in the dual problem of the form co - programming model, as shown in Equation (30):

[0038]

[0039] Equation (30) defines the linear Lagrangian equations for various electricity products.

[0040] As a preferred embodiment of the present invention: taking the partial derivative of each variable in Equation (30), the process is as follows:

[0041]

[0042] Equations (31) and (32) are obtained by taking the derivatives of Equation (30) with respect to power and inertia respectively, and Equations (33) and (34) are obtained by taking the partial derivatives of Equation (30) with respect to the forced frequency response and the fixed frequency response respectively.

[0043] In Equation (31), after calculating the partial derivative, the power balance equation simplifies to one term on both sides, thus preventing the further application of the KKT conditions.

[0044] As a preferred embodiment of the present invention: for Equations (32)-(34), by setting the partial derivatives to zero, the KKT conditions still apply, and the modified service price form is as follows:

[0045]

[0046] In the formula, T EFR is the time of the forced frequency response;

[0047] Equations (35), (36), and (37) respectively represent the subsidy prices for units providing inertia, forced frequency response, and fixed frequency response. Based on the price, the joint market subsidizes all market participants to incentivize the optimal allocation of frequency resources.

[0048] As a preferred embodiment of the present invention: The goal of the planning model is to minimize the sum of the annual operating cost and the investment cost of the energy storage system. The objective function is as follows:

[0049] minCost = C Inv + C Ope (95)

[0050] Wherein, C Inv is the total investment cost of the energy storage system, and C Ope is the total operating cost;

[0051] The calculation formula for the total investment cost of the energy storage system is as follows:

[0052]

[0053] Wherein, is the construction cost coefficient of the energy storage system, and S e is the capacity construction of the energy storage system;

[0054] The calculation formula for the total operating cost of the energy storage system is as follows:

[0055]

[0056] Wherein, N Day is the number of operating days, c E is the energy cost coefficient, c H is the inertia cost coefficient, c EFR is the cost coefficient of forced frequency response, c PFR is the cost coefficient of fixed frequency response, and ρ y is the weight of each typical scenario;

[0057] Equation (40) verifies that under 365 operating days, the annual operating cost consists of the revenues of each unit and the energy storage system participating in the energy-frequency joint ancillary service;

[0058] In the planning model, the installed capacity of the energy storage system is regarded as a variable and is determined during the process of minimizing the annual operating and investment costs;

[0059] Equation (41) ensures that the energy storage system cannot charge and discharge simultaneously. Equations (42)-(43) limit the number of state transitions in the operation of the energy storage system. Equation (44 constrains the energy stored in the energy storage system. Equation (45) restricts the initial and end states of the energy storage system to ensure the optimal utilization of energy. Equations (46) and (47) set the maximum and minimum charge-discharge power limits of the energy storage system. Equations (48) and (49) limit the maximum forced frequency response and fixed frequency response regulations for each:

[0060]

[0061]

[0062] where S e is the construction capacity of the energy storage system, and S e,t,y is the capacity demand of the energy storage system at time t in scenario y, is the maximum value of the energy storage system capacity in scenario y, and are the maximum or minimum capacities required for the energy storage system, respectively. S cap is the capacity constraint of the energy storage system, is the initial capacity of the energy storage system at time t in scenario y, is the end capacity of the energy storage system at time t in scenario y, and are the constraint conditions for the charge-discharge state switching of the energy storage system, respectively;

[0063] Equation (50) limits the maximum and minimum capacities of each energy storage system. Equation (51) restricts the maximum capacity investment of the entire system. Equations (52) and (53) set the minimum charge-discharge power of each energy storage system. Equations (54) and (55) establish the maximum charge-discharge power limit. Equation (56) determines the capacity demand of the energy storage system under each typical scenario. Equation (57) calculates the optimized construction plan by weighting the capacity demands of multiple scenarios.

[0064] Compared with the prior art, the beneficial effects of the present invention are:

[0065] The present invention discloses a method for an energy storage system to participate in the combined energy and frequency ancillary service market, which has significant technical advantages and application value in enhancing the profits of the energy storage system while participating in both the energy market and the ancillary service market. This method creatively proposes an investment planning model for the energy storage system considering the unit commitment with short-term security constraints. This model determines the optimal investment method for the energy storage system and integrates the unit commitment model with short-term security constraints into the investment planning of the energy storage system, ensuring the feasibility of the long-term investment method in short-term operations and effectively reducing the operation risks in actual operation. In terms of participating in the combined energy and frequency ancillary service market mechanism, the combined energy and frequency ancillary service market is introduced, and the revenue of the energy storage system in the combined market is used as an indicator to evaluate different investment methods. Through a reasonable pricing mechanism, it guides the energy storage system and traditional thermal power units to orderly provide inertia and frequency response services, achieving the optimal allocation of frequency regulation resources. Finally, it deeply analyzes the influence of various factors on the investment planning results of the energy storage system, and details the influence of factors such as the frequency response ability of the energy storage system, the renewable energy penetration rate, and the frequency safety margin of the system on the investment planning results, providing a quantitative basis for market design and investment methods. Through numerical studies, the importance and effectiveness of the proposed model in determining the optimal investment method for the energy storage system and guiding system operation are verified, providing valuable reference for power system operators and decision-makers.

[0066] The core innovation of this method lies in proposing an investment planning model for the energy storage system considering short-term security constraints, which not only retains the operating constraints of traditional generators and energy storage systems but also ensures the safety of the operation of generators and energy storage systems through short-term security constraints. The unit commitment model considering short-term security constraints proposes an optimal investment strategy planning model for the energy storage system to support the frequency security of the system with a high renewable energy penetration rate under various typical scenarios. To better allocate the frequency regulation capacity of the energy storage system, this application establishes a combined energy and frequency ancillary service market to incentivize the energy storage system to provide frequency support for the power system, plans two optimal investment strategies for the energy storage system, namely the energy storage system capacity and the maximum frequency response capacity of the energy storage system in different markets, and optimally utilizes the frequency regulation resources of the energy storage system to meet the requirements of the high renewable penetration system for inertia and frequency response. This application provides an effective market mechanism for stimulating energy storage investment and is of great significance for determining the optimal investment plan and guiding system operation. Brief Description of the Drawings

[0067] Figure 1 It is a flowchart of the method of the present invention. Detailed Embodiment

[0068] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0069] Embodiment 1

[0070] As Figure 1 shown, the present invention provides a method for an energy storage system to participate in the joint energy and frequency ancillary service market. The method includes the following steps:

[0071] (1) An investment planning model for an energy storage system considering a short-term security-constrained unit commitment model;

[0072] Specifically, the above step (1) an investment planning model for an energy storage system considering a short-term security-constrained unit commitment model is described in detail as follows:

[0073] An investment planning model for an energy storage system considering a short-term security-constrained unit commitment model covers three core aspects: integration of short-term operation constraints of units, balance between security and economy, and establishment of a mathematical model of the energy storage system.

[0074] In the integration of short-term operation constraints of units, the short-term security-constrained unit commitment model is integrated into the investment planning of the energy storage system. Considering the frequency security of the power grid and the safe operation constraints of generators and the energy storage system, the safe operation of generators and the energy storage system is ensured, and the operation constraint conditions considering safety for the energy storage system and generators are formed.

[0075] Based on the establishment of the above-mentioned operation constraint conditions considering safety for the energy storage system and generators, the balance between frequency security and economy is ensured. While meeting the system frequency security requirements, the model optimizes the investment cost and operation cost of the energy storage system. By simulating multiple typical scenarios and comprehensively considering the system requirements under different operation conditions, the optimal investment strategy for the energy storage system is determined.

[0076] Finally, a mathematical model of the energy storage system is established, with the maximum benefit of the energy storage system as the objective function and the charging power, discharging power, etc. of the energy storage system as optimization variables to establish the mathematical model of the energy storage system.

[0077] (2) Introduction of a joint energy and frequency ancillary service market mechanism;

[0078] Specifically, the above step (2) the introduction of a joint energy and frequency ancillary service market mechanism is described in detail below:

[0079] An energy storage system investment planning model considering a unit commitment model with short-term security constraints covers three core aspects: constructing an integrated ancillary service market, reasonably allocating frequency regulation resources, and improving the revenue and investment efficiency of the energy storage system.

[0080] In constructing the integrated ancillary service market, the designed joint market includes four flexibility products: energy, inertia, forced frequency response, and fixed frequency response, providing economic incentives for the energy storage system to participate in frequency regulation, ensuring the quality of frequency regulation, and making full use of the frequency response capacity of the energy storage system.

[0081] On the basis of constructing the integrated ancillary service market, reasonably allocate frequency regulation resources. Based on the pricing mechanism of the Lagrange duality theorem and KKT conditions, determine the marginal price and subsidy price of various electricity products, and reasonably allocate the frequency regulation resources of the energy storage system and traditional thermal power units.

[0082] Finally, improve the revenue and investment efficiency of the energy storage system. The energy storage system obtains revenue from the energy market and the frequency ancillary service market through the joint market. Compared with the energy storage system that only participates in the energy market, the revenue of the energy storage system participating in the joint market increases significantly, and the investment cost decreases.

[0083] (3) A method for deeply analyzing the influence of various factors on the investment planning of the energy storage system.

[0084] Specifically, the method in the above step (3) for deeply analyzing the influence of various factors on the investment planning of the energy storage system is described in detail below:

[0085] Evaluate the influence of the frequency response capacity of the energy storage system. By analyzing the impact of the change in the maximum frequency response capacity of the energy storage system on the investment planning of the energy storage system, including the capacity demand of the energy storage system, social welfare, investment payback period, etc., determine the optimal capacity range to minimize the capacity demand of the energy storage system, maximize social welfare, and shorten the investment payback period.

[0086] Determine the optimal level of renewable energy penetration. Study the influence of different renewable energy penetrations on the investment strategy of the energy storage system, and determine the best value of renewable energy penetration to maximize the revenue of the energy storage system and optimize the utilization of the frequency regulation resources of the energy storage system.

[0087] Optimize the setting of the system frequency safety margin. Explore the influence of the system frequency safety margin on the investment planning of the energy storage system, and determine the best setting value of the frequency safety margin to achieve relatively high levels of both the revenue of the energy storage system and the utilization rate of renewable energy, indicating that this is the optimal setting of the frequency safety margin.

[0088] Example 2;

[0089] The present invention will be further described in detail below with reference to the accompanying drawings. A method for an energy storage system to participate in the energy and frequency joint ancillary service market provided by this embodiment is described in the following specific implementation manner.

[0090] (1) An investment planning model for an energy storage system considering a short-term security-constrained unit commitment model is described in detail as follows:

[0091] The short-term unit commitment constraints are as follows:

[0092]

[0093]

[0094] In the formula, is the minimum output of the traditional thermal unit, is the maximum output of the traditional thermal unit, P g,t,y is the output of the conventional thermal unit at time t in scenario y, is the binary variable of the operating state of the conventional thermal unit at time t in scenario y, is the binary variable of the start-up state of the conventional thermal unit at time t in scenario y, is the binary variable of the shutdown state of the conventional thermal unit at time t in scenario y, is the ramping power of the traditional thermal unit, is the binary variable of the frequency regulation condition of the conventional thermal unit at time t in scenario y.

[0095] Equation (1) constrains the output of the traditional thermal power unit. Equation (2) constrains the change of the binary variable of the operating condition of the thermal power unit. Equations (3)-(4) define the start-up and shutdown constraints of the thermal generator. Equation (5) imposes the ramp constraint. Equation (7) gives the output limit of the renewable energy. Equation (8) reflects that the thermal power unit can provide ancillary services only when it is in the operating state.

[0096] To ensure the frequency security of the system with a high renewable energy penetration rate, the planning model considers the inertia and frequency regulation support of the energy storage system under short-term security constraints.

[0097]

[0098]

[0099] In the formula, is the charging power of the energy storage system at time t in scenario y, is the charging power of the energy storage system at time t in scenario y, is the load at time t in scenario y, is the maximum output of the renewable energy unit at time t in scenario y, P r,t,yOutput of renewable energy units at time t in scenario y Maximum output of renewable energy units Frequency safety margin Frequency regulation power required at time t in scenario y Energy price at time t in scenario y Inertia price at time t in scenario y Price of forced frequency response at time t in scenario y Price of fixed frequency response at time t in scenario y Dual variable of the frequency change rate equation at time t in scenario y Dual variable of the frequency nadir equation at time t in scenario y Dual variable of the Q - S - S equation at time t in scenario y Binary variable for the charging or discharging condition of the energy storage system at time t in scenario y Binary variable for the frequency regulation condition of the conventional thermal unit at time t in scenario y Binary variable for the frequency regulation condition of the renewable energy unit at time t in scenario y Binary variable for the charging condition of the energy storage system at time t in scenario y Binary variable for the discharging condition of the energy storage system at time t in scenario y, H e,t,y Inertia of the bid at time t in scenario y, H g,t,y Bidding inertia of the conventional thermal unit at time t in scenario y, H r,t,y Bidding inertia of the renewable energy generator set at time t in scenario y Total inertia at time t in scenario y Inertia constant of the renewable energy unit at time t in scenario y, D e,t,y D r,t,y Droop coefficient of the renewable energy unit, D g,t,y Droop coefficient of the unit at time t in scenario y Droop coefficient limit at time t in scenario y Total droop coefficient at time t in scenario y Coefficient of the frequency safety margin equation, Δf max Frequency nadir, f0 is the base frequency Total forced frequency response, EFR g,t,y Bidding of the forced frequency response of the conventional thermal unit at time t in scenario y, EFR e,t,y Bidding of the forced frequency response of the energy storage system at time t in scenario y is the total fixed frequency response, PFR g,t,y is the fixed frequency response bidding of the energy storage system at time t in scenario y, PFR e,t,y is the fixed frequency response bidding of the energy storage system at time t in scenario y, RoCoF max is the rate of change of frequency, T PFR is the time of the fixed frequency response.

[0100] Equation (9) represents the power balance equation of the system, and its dual variable is the energy market price. Equations (10) and (11) respectively represent the forced frequency response and fixed frequency response generated by the energy storage system and the thermal generator. Equation (12) is the reserve equation of the renewable energy unit. Equation (13) restricts the conditions for the thermal power unit and the renewable energy unit to participate in frequency regulation. Equation (14) constrains the bidding inertia of the renewable energy unit. Equation (15) restricts the droop coefficient provided by the renewable energy. Equation (16) reflects the total inertia of the system. Equation (17) is the frequency safety margin constraint of the power system. Equations (18)-(19) constrain the total droop constant of the system. Equation (20) ensures that the rate of change of the system frequency remains within the safe range. Equation (21) is the quasi-steady state frequency constraint. Equation (22) restricts the lowest point of the system frequency simplified from the second-order cone constraint.

[0101] (2) Introduce a combined energy and frequency ancillary service market mechanism; the details are as follows:

[0102] This application introduces a combined energy and ancillary service market mechanism, where the ancillary service market includes inertia, forced frequency response, and fixed frequency response. The pricing strategy is based on the Lagrange dual theorem and the KKT conditions, and can reflect the actual demand of the system for various ancillary services. The revenue of the energy storage system in the combined market is an evaluation index for determining the optimal investment strategy of the energy storage system.

[0103] Equations (9)-(11), (16), (20)-(22) illustrate the ability of market participants to provide specific power services and the real-time demand of the system for these services. The dual variables of these equations reveal the real-time value of various resource endowments. On this basis, this application proposes a subsidy mechanism for various power products in the combined market.

[0104] Use the Lagrange dual theorem to reformulate the equations, where the Lagrange multipliers are used as dual variables. These variables indicate the increase in system cost associated with integrating additional units of specific electrical products. The corresponding Lagrange equations are as follows:

[0105]

[0106] Equation (23) is the Lagrange equation of Equation (9). Equation (24) is the Lagrange equation of Equation (14). Equation (25) is the Lagrange equation of Equation (10). Equation (26) is the Lagrange equation of Equation (11). Equation (27) is the Lagrange equation of Equation (20). Equation (28) is the Lagrange equation of Equation (21). Equation (29) is the Lagrange equation of Equation (22).

[0107] Using the Lagrange duality theorem, the clearing value equation of the joint market and the subsidy equation for providing ancillary services are obtained. Equations. Equations (23)-(26) represent the marginal price required for market participants to produce an additional unit of each electricity product. Equations (27)-(29) reflect the cost required to improve the system security constraint performance by one unit. According to the duality theorem, each term in these equations, including the Lagrange dual multiplier, can be expressed by the Lagrange equation in the dual problem of the form co - planning model, as shown in Equation (30).

[0108]

[0109] Equation (30) defines the linear Lagrange equation for various electricity products. Since the unit commitment model is established and the binary variables of each unit are solved, this equation describes a convex optimization problem, which can be solved using the KKT conditions. Therefore, this study uses the KKT conditions based on the system - optimal principle to determine the pricing strategy. The specific derivative method is to take the partial derivative of each variable in Equation (30). The detailed derivation process is as follows:

[0110]

[0111] Equations (31) and (32) are obtained by taking the derivatives of Equation (30) with respect to power and inertia respectively. Equations (33) and (34) are obtained from the partial derivatives of Equation (30) with respect to the forced frequency response and the fixed frequency response respectively.

[0112] In Equation (31), after calculating the partial derivative, the power balance equation simplifies to one term on both sides, which prevents the further application of the KKT conditions. Therefore, this study uses the binary variables in the power balance equation to represent the marginal clearing price of energy. For Equations (32)-(34), by setting the partial derivatives to zero, the KKT conditions still apply, which directly reveals the optimal prices of inertia, EFR, and PFR. The modified service price form is as follows:

[0113]

[0114]

[0115] where T EFR is the time of the forced frequency response.

[0116] Equations (35), (36) and (37) respectively represent the subsidy prices for units providing inertia, forced frequency response, and fixed frequency response. Based on the price, the joint market subsidizes all market participants to incentivize the optimal allocation of frequency resources.

[0117] (3) A method for in-depth analysis of the impact of multiple factors on the investment planning of energy storage systems; details are as follows:

[0118] The goal of the planning model is to minimize the sum of the annual operating cost and the investment cost of the energy storage system. The objective function is as follows.

[0119] minCost = C Inv + C Ope (152)

[0120] In the formula, C Inv is the total investment cost of the energy storage system, and C Ope is the total operating cost.

[0121] The calculation formula for the total investment cost of the energy storage system is as follows:

[0122]

[0123] In the formula, is the construction cost coefficient of the energy storage system, and S e is the capacity construction of the energy storage system.

[0124] The calculation formula for the total operating cost of the energy storage system is as follows:

[0125]

[0126] In the formula, N Day is the number of operating days, c E is the energy cost coefficient, c H is the inertia cost coefficient, c EFR is the cost coefficient of forced frequency response, c PFR is the cost coefficient of fixed frequency response, and ρ y is the weight of each typical scenario.

[0127] Equation (40) verifies that under 365 operating days, the annual operating cost consists of the revenues of each unit and the energy storage system participating in the energy-frequency joint ancillary service.

[0128] In the planning model, the installed capacity of the energy storage system is regarded as a variable and is determined in the process of minimizing the annual operating and investment costs.

[0129] Equation (41) ensures that the energy storage system cannot charge and discharge simultaneously. Equations (42)-(43) limit the number of state transitions of the energy storage system operation. Equation (44) imposes a constraint on the energy stored in the energy storage system. Equation (45) restricts the initial and end states of the energy storage system to ensure optimal utilization of energy. Equations (46) and (47) set the maximum and minimum charge-discharge power limits of the energy storage system. Equations (48) and (49) limit the maximum forced frequency response and fixed frequency response regulations for each one.

[0130]

[0131]

[0132] Wherein, S e is the construction capacity of the energy storage system, S e,t,y is the capacity demand of the energy storage system at time t in scenario y, is the maximum value of the energy storage system capacity in scenario y, and are the maximum or minimum capacities required for the energy storage system respectively, S cap is the capacity constraint of the energy storage system, is the initial capacity of the energy storage system at time t in scenario y, is the end capacity of the energy storage system at time t in scenario y, and are the constraint conditions for the charge-discharge state switching of the energy storage system respectively.

[0133] Equation (50) limits the maximum and minimum capacities of each energy storage system. Equation (51) limits the maximum capacity investment of the entire system. Equations (52) and (53) set the minimum charge-discharge power of each energy storage system. Equations (54) and (55) establish the maximum charge-discharge power limit. Equation (56) determines the capacity demand of the energy storage system under each typical scenario. Equation (57) calculates the optimized construction plan by weighting the capacity demands of multiple scenarios.

[0134] A method for an energy storage system to participate in the joint energy and frequency ancillary service market proposed by the present invention provides new technical support and decision-making basis for the energy storage system to participate in the energy market and ancillary service market, and shows significant and multi-dimensional effects in practical applications. From the perspective of the safe operation of power generation units, by introducing a short-term unit commitment model with security constraints, integrating the short-term security-constrained unit commitment model into the investment planning of the energy storage system, and comprehensively considering factors such as frequency security, the operation safety of generators and energy storage systems, etc., it ensures the feasibility of the long-term investment method in short-term operations and effectively reduces the operation risks in actual operations. In terms of the investment planning of the energy storage system, considering various influencing factors, the impacts of factors such as the frequency response ability of the energy storage system, the renewable energy penetration rate, and the frequency security margin of the system on the investment planning results are analyzed in detail, providing a quantitative basis for market design and investment methods. In addition, for the energy storage system, a joint market is constructed, introducing a joint energy and frequency ancillary service market, including four flexibility products: energy, inertia, fixed frequency response, and forced frequency response, providing economic incentives for the energy storage system to participate in frequency regulation. By optimizing resource allocation, the revenue of the energy storage system in the joint market is used as an indicator to evaluate different investment methods. Through a reasonable pricing mechanism, it guides the energy storage system and traditional thermal power units to orderly provide inertia and frequency response services, achieving the optimal allocation of frequency regulation resources. On the premise of meeting the system's frequency security requirements, compared with the energy storage system that only participates in the energy market, the energy storage system participating in the joint market can plan a smaller capacity, thereby reducing the construction investment of the energy storage system and lowering the overall investment cost.

[0135] The present invention has achieved excellent results in improving the safe operation of power generation units and promoting the investment planning of energy storage systems to participate in the energy market and ancillary service market, and has broad application prospects and important promotion value.

[0136] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to embrace all changes within the meaning and scope of the equivalent elements of the claims in the present invention. Any reference signs in the claims should not be regarded as limiting the claimed rights.

[0137] In addition, it should be understood that although this specification is described in terms of embodiments, not every embodiment contains only an independent technical solution. This narrative style of the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for an energy storage system to participate in the combined energy and frequency ancillary service market, characterized in that It includes the following steps: (1) Consider the investment planning model of the energy storage system for the short-term security-constrained unit commitment model: Integrate the short-term operation constraints of the units, and consider the frequency security of the power grid and the safe operation constraints of the generators and the energy storage system; Based on the above constraints, establish a model to ensure the balance between frequency security and economy, and optimize the investment cost and operation cost of the energy storage system; Determine the optimal investment strategy of the energy storage system by simulating multiple typical scenarios; Establish a mathematical model of the energy storage system, with the maximum benefit of the energy storage system as the objective function and the charging power and discharging power as the optimization variables; (2) Introduce the joint energy and frequency ancillary service market mechanism: Construct a comprehensive ancillary service market, including four flexibility products: energy, inertia, fixed frequency response, and forced frequency response, to provide economic incentives for the energy storage system; Based on the pricing mechanism of the Lagrange dual theorem and the KKT conditions, reasonably allocate the frequency regulation resources of the energy storage system and traditional thermal power units; Improve the benefit and investment efficiency of the energy storage system. The energy storage system obtains the benefits of the energy market and the frequency ancillary service market through the joint market; (3) Method for deeply analyzing the influence of various factors on the investment planning of the energy storage system: Evaluate the influence of the frequency response ability of the energy storage system, determine the optimal ability range, so that the capacity demand of the energy storage system is the smallest, the social welfare is the largest, and the investment payback period is the shortest; Determine the optimal level of the renewable energy penetration rate to maximize the benefit of the energy storage system and optimize the utilization of the frequency regulation resources; Optimize the setting of the system frequency security margin and determine the best setting value.

2. A method for an energy storage system to participate in the energy and frequency joint ancillary service market according to claim 1, wherein The short-term operation constraints of the units are as follows: wherein, is the minimum output of the traditional thermal unit, is the maximum output of the traditional thermal unit, P g,t,y is the output of the conventional thermal unit at time t in scenario y, is a binary variable of the operating state of the conventional thermal unit at time t in scenario y, is a binary variable of the starting state of the conventional thermal unit at time t in scenario y, is a binary variable of the shutdown state of the conventional thermal unit at time t in scenario y, is the ramp power of the traditional thermal unit, is a binary variable of the frequency regulation condition of the conventional thermal unit at time t in scenario y; Equation (1) constrains the output of traditional thermal power units, Equation (2) constrains the change of the binary variable of the operating condition of the thermal power unit, Equations (3)-(4) define the start-up and shutdown constraints of the thermal generator, Equation (5) imposes a ramp constraint, Equation (7) gives the output limit of renewable energy, and Equation (8) reflects that the thermal power unit can provide ancillary services only when it is in the operating state.

3. A method for an energy storage system to participate in the energy and frequency joint ancillary service market according to claim 2, characterized in that, The planning model considering the inertia and frequency regulation support of the energy storage system under short-term security constraints is as follows: Wherein, is the charging power of the energy storage system at time t in scenario y, is the charging power of the energy storage system at time t in scenario y, is the load at time t in scenario y, is the maximum output of the renewable energy unit at time t in scenario y, P r,t,y is the output of the renewable energy unit at time t in scenario y, is the maximum output of the renewable energy unit, is the frequency safety margin, is the frequency regulation power required at time t in scenario y, is the energy price at time t in scenario y, is the inertia price at time t in scenario y, is the price of the forced frequency response at time t in scenario y, is the price of the fixed frequency response at time t in scenario y, is the dual variable of the frequency change rate equation at time t in scenario y, is the dual variable of the frequency lowest point equation at time t in scenario y, is the dual variable of the Q-S-S equation at time t in scenario y, is the binary variable of the charging or discharging condition of the energy storage system at time t in scenario y, is the binary variable of the frequency regulation condition of the traditional thermal unit at time t in scenario y, is the binary variable of the frequency regulation condition of the renewable energy unit at time t in scenario y, is the binary variable of the charging condition of the energy storage system at time t in scenario y, is the binary variable of the discharging condition of the energy storage system at time t in scenario y, H e,t,y is the inertia of the bid at time t in scenario y, H g,t,y The bidding inertia of the traditional thermal unit at time t in scenario y, H r,t,y is the bidding inertia of the renewable energy generating unit at time t in scenario y, is the total inertia at time t in scenario y, is the inertia constant of the renewable energy unit at time t in scenario y, D e,t,y D r,t,y is the droop coefficient of the renewable energy unit, D g,t,y is the droop coefficient of the unit at time t in scenario y, is the droop coefficient limit at time t in scenario y, is the total droop coefficient at time t in scenario y, is the coefficient of the frequency safety margin equation, Δf max is the lowest frequency point, f0 is the base frequency, is the total forced frequency response, EFR g,t,y is the forced frequency response bid of the conventional thermal unit at time t in scenario y, EFR e,t,y is the forced frequency response bid of the energy storage system at time t in scenario y, is the total fixed frequency response, PFR g,t,y is the fixed frequency response bid of the energy storage system at time t in scenario y, PFR e,t,y is the fixed frequency response bid of the energy storage system at time t in scenario y, RoCoF max is the rate of change of frequency, T PFR is the time of the fixed frequency response; Equation (9) represents the power balance equation of the system, and its dual variable is the energy market price. Equations (10) and (11) respectively represent the forced frequency response and fixed frequency response generated by the energy storage system and the thermal generator. Equation (12) is the reserve equation of the renewable energy unit. Equation (13) restricts the conditions for the thermal power unit and the renewable energy unit to participate in frequency modulation. Equation (14) constrains the bidding inertia of the renewable energy unit. Equation (15) restricts the droop coefficient provided by the renewable energy. Equation (16) reflects the total inertia of the system. Equation (17) is the frequency security margin constraint of the power system. Equations (18)-(19) constrain the total droop constant of the system. Equation (20) ensures that the frequency change rate of the system remains within the safe range. Equation (21) is the quasi-steady state frequency constraint. Equation (22) restricts the lowest point of the system frequency simplified from the second-order cone constraint.

4. A method for an energy storage system to participate in the energy and frequency joint ancillary service market according to claim 3, characterized in that, Use the Lagrange dual theorem to reformulate the equation, where the Lagrange multiplier is used as the dual variable, and the corresponding Lagrange equation is as follows: Equation (23) is the Lagrangian equation of Equation (9), Equation (24) is the Lagrangian equation of Equation (14), Equation (25) is the Lagrangian equation of Equation (10), Equation (26) is the Lagrangian equation of Equation (11), Equation (27) is the Lagrangian equation of Equation (20), Equation (28) is the Lagrangian equation of Equation (21), and Equation (29) is the Lagrangian equation of Equation (22); Equations (23)-(26) represent the marginal price required for market participants to produce an additional unit of each electricity product. Equations (27)-(29) reflect the cost required to improve the system security constraint performance by one unit. According to the duality theorem, each term in these equations, including the Lagrangian dual multiplier, can be expressed by the Lagrangian equation in the dual problem of the co-formulation model, as shown in Equation (30): Equation (30) defines the linear Lagrangian equations for various electricity products.

5. A method for an energy storage system to participate in the energy and frequency joint ancillary service market according to claim 4, characterized in that, Take the partial derivatives of each variable in Equation (30) as follows: Equations (31) and (32) are obtained by taking the derivatives of Equation (30) with respect to power and inertia respectively. Equations (33) and (34) are obtained by taking the partial derivatives of Equation (30) with respect to the forced frequency response and the fixed frequency response respectively; In Equation (31), after calculating the partial derivative, the power balance equation simplifies to one term on both sides, thus preventing the further application of the KKT conditions.

6. A method for an energy storage system to participate in the energy and frequency joint ancillary service market according to claim 5, characterized in that For Equations (32)-(34), by setting the partial derivatives to zero, the KKT conditions still apply, and the modified service price form is as follows: Where T EFR is the time for forced frequency response; Equations (35), (36), and (37) represent the subsidy prices for the units providing inertia, forced frequency response, and fixed frequency response respectively. The joint market subsidizes all market participants based on the price to incentivize the optimal allocation of frequency resources.

7. A method for an energy storage system to participate in the energy and frequency joint ancillary service market according to claim 6, characterized in that The objective of the planning model is to minimize the sum of the annual operating cost and the investment cost of the energy storage system. The objective function is as follows: minCost = C Inv + C Ope (38) Where, C Inv is the total investment cost of the energy storage system, and C Ope is the total operating cost; The calculation formula for the total investment cost of the energy storage system is as follows: In the formula, is the construction cost coefficient of the energy storage system, and S e is the capacity construction of the energy storage system; The calculation formula for the total operating cost of the energy storage system is as follows: Where N Day is the number of operating days, c E is the energy cost coefficient, c H is the inertia cost coefficient, c EFR is the cost coefficient of the forced frequency response, c PFR is the cost coefficient of the fixed frequency response, ρ y is the weight of each typical scenario; Equation (40) verifies that under 365 operating days, the annual operating cost consists of the revenues of each unit and the energy storage system participating in the energy-frequency joint ancillary service; In the planning model, the installed capacity of the energy storage system is regarded as a variable and is determined in the process of minimizing the annual operating and investment costs; Equation (41) ensures that the energy storage system cannot charge and discharge simultaneously. Equations (42)-(43) limit the number of state transitions of the energy storage system operation. Equation (44) constrains the energy stored in the energy storage system. Equations (45) limit the initial and end states of the energy storage system to ensure the optimal utilization of energy. Equations (46) and (47) set the maximum and minimum charge and discharge power limits of the energy storage system. Equations (48) and (49) limit the maximum forced frequency response and fixed frequency response regulations for each; Where, S e is the construction capacity of the energy storage system, S e,t,y is the capacity demand of the energy storage system at time t in scenario y, is the maximum value of the energy storage system capacity in scenario y, and are the maximum or minimum capacities required by the energy storage system respectively, S cap is the capacity constraint of the energy storage system, is the initial capacity of the energy storage system at time t in scenario y, is the end capacity of the energy storage system at time t in scenario y, and are the constraint conditions for the charge-discharge state switching of the energy storage system respectively; Equation (50) limits the maximum and minimum capacities of each energy storage system. Equation (51) limits the maximum capacity investment of the entire system. Equations (52) and (53) set the minimum charge and discharge power of each energy storage system. Equations (54) and (55) establish the maximum charge and discharge power limits. Equation (56) determines the capacity requirements of the energy storage system under each typical scenario. Equation (57) calculates the optimized construction plan by weighting the capacity requirements of multiple scenarios.

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